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Concept: Regression analysis


The most widely used task functional magnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumptions. In this work, we use real resting-state data and a total of 3 million random task group analyses to compute empirical familywise error rates for the fMRI software packages SPM, FSL, and AFNI, as well as a nonparametric permutation method. For a nominal familywise error rate of 5%, the parametric statistical methods are shown to be conservative for voxelwise inference and invalid for clusterwise inference. Our results suggest that the principal cause of the invalid cluster inferences is spatial autocorrelation functions that do not follow the assumed Gaussian shape. By comparison, the nonparametric permutation test is found to produce nominal results for voxelwise as well as clusterwise inference. These findings speak to the need of validating the statistical methods being used in the field of neuroimaging.

Concepts: Scientific method, Regression analysis, Mathematics, Medical imaging, Magnetic resonance imaging, Multiple comparisons, Statistical inference, Familywise error rate


Despite the many number of studies examining workaholism, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (Mage = 37.3 years, SD = 11.4, range = 16-75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Correlations between workaholism and all psychiatric disorder symptoms were positive and significant. Workaholism comprised the dependent variable in a three-step linear multiple hierarchical regression analysis. Basic demographics (age, gender, relationship status, and education) explained 1.2% of the variance in workaholism, whereas work demographics (work status, position, sector, and annual income) explained an additional 5.4% of the variance. Age (inversely) and managerial positions (positively) were of most importance. The psychiatric symptoms (ADHD, OCD, anxiety, and depression) explained 17.0% of the variance. ADHD and anxiety contributed considerably. The prevalence rate of workaholism status was 7.8% of the present sample. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with being a workaholic. The independent variables explained between 6.1% and 14.4% in total of the variance in workaholism cases. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible psychiatric predictors of workaholism, and particularly shed new insight into the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed.

Concepts: Psychology, Regression analysis, Addiction, Mental disorder, Psychiatry


The exact timing, route, and process of the initial peopling of the Americas remains uncertain despite much research. Archaeological evidence indicates the presence of humans as far as southern Chile by 14.6 thousand years ago (ka), shortly after the Pleistocene ice sheets blocking access from eastern Beringia began to retreat. Genetic estimates of the timing and route of entry have been constrained by the lack of suitable calibration points and low genetic diversity of Native Americans. We sequenced 92 whole mitochondrial genomes from pre-Columbian South American skeletons dating from 8.6 to 0.5 ka, allowing a detailed, temporally calibrated reconstruction of the peopling of the Americas in a Bayesian coalescent analysis. The data suggest that a small population entered the Americas via a coastal route around 16.0 ka, following previous isolation in eastern Beringia for ~2.4 to 9 thousand years after separation from eastern Siberian populations. Following a rapid movement throughout the Americas, limited gene flow in South America resulted in a marked phylogeographic structure of populations, which persisted through time. All of the ancient mitochondrial lineages detected in this study were absent from modern data sets, suggesting a high extinction rate. To investigate this further, we applied a novel principal components multiple logistic regression test to Bayesian serial coalescent simulations. The analysis supported a scenario in which European colonization caused a substantial loss of pre-Columbian lineages.

Concepts: DNA, Regression analysis, United States, Brazil, South America, Americas, Latin America, Indigenous peoples of the Americas


Fructose has been implicated in the pathogenesis of obesity and type 2 diabetes. In contrast to glucose, CNS delivery of fructose in rodents promotes feeding behavior. However, because circulating plasma fructose levels are exceedingly low, it remains unclear to what extent fructose crosses the blood-brain barrier to exert CNS effects. To determine whether fructose can be endogenously generated from glucose via the polyol pathway (glucose → sorbitol → fructose) in human brain, 8 healthy subjects (4 women/4 men; age, 28.8 ± 6.2 years; BMI, 23.4 ± 2.6; HbA1C, 4.9% ± 0.2%) underwent (1)H magnetic resonance spectroscopy scanning to measure intracerebral glucose and fructose levels during a 4-hour hyperglycemic clamp (plasma glucose, 220 mg/dl). Using mixed-effects regression model analysis, intracerebral glucose rose significantly over time and differed from baseline at 20 to 230 minutes. Intracerebral fructose levels also rose over time, differing from baseline at 30 to 230 minutes. The changes in intracerebral fructose were related to changes in intracerebral glucose but not to plasma fructose levels. Our findings suggest that the polyol pathway contributes to endogenous CNS production of fructose and that the effects of fructose in the CNS may extend beyond its direct dietary consumption.

Concepts: Central nervous system, Regression analysis, Brain, Nutrition, Diabetes mellitus, Glucose, Diabetes, Human brain


BACKGROUND: The aim of this study is to compare the odds of postpartum haemorrhage among women who opt for home birth against the odds of postpartum haemorrhage for those who plan a hospital birth. It is an observational study involving secondary analysis of maternity records, using binary logistic regression modelling. The data relate to pregnancies that received maternity care from one of fifteen hospitals in the former North West Thames Regional Health Authority Area in England, and which resulted in a live or stillbirth in the years 1988–2000 inclusive, excluding ‘high-risk’ pregnancies, unplanned home births, pre-term births, elective Caesareans and medical inductions. RESULTS: Even after adjustment for known confounders such as parity, the odds of postpartum haemorrhage (>=1000ml of blood lost) are significantly higher if a hospital birth is intended than if a home birth is intended (odds ratio 2.5, 95% confidence interval 1.7 to 3.8). The ‘home birth’ group included women who were transferred to hospital during labour or shortly after birth. CONCLUSIONS: Women and their partners should be advised that the risk of PPH is higher among births planned to take place in hospital compared to births planned to take place at home, but that further research is needed to understand (a) whether the same pattern applies to the more life-threatening categories of PPH, and (b) why hospital birth is associated with increased odds of PPH. If it is due to the way in which labour is managed in hospital, changes should be made to practices which compromise the safety of labouring women.

Concepts: Regression analysis, Logit, Logistic regression, Pregnancy, Childbirth, Obstetrics, Midwifery, Home birth


Correctly assessing a scientist’s past research impact and potential for future impact is key in recruitment decisions and other evaluation processes. While a candidate’s future impact is the main concern for these decisions, most measures only quantify the impact of previous work. Recently, it has been argued that linear regression models are capable of predicting a scientist’s future impact. By applying that future impact model to 762 careers drawn from three disciplines: physics, biology, and mathematics, we identify a number of subtle, but critical, flaws in current models. Specifically, cumulative non-decreasing measures like the h-index contain intrinsic autocorrelation, resulting in significant overestimation of their “predictive power”. Moreover, the predictive power of these models depend heavily upon scientists' career age, producing least accurate estimates for young researchers. Our results place in doubt the suitability of such models, and indicate further investigation is required before they can be used in recruiting decisions.

Concepts: Scientific method, Regression analysis, Linear regression, Prediction, Futurology, Future, Science, Forecasting


Thousands of lives are lost every year in developing countries for failing to detect epidemics early because of the lack of real-time disease surveillance data. We present results from a large-scale deployment of a telephone triage service as a basis for dengue forecasting in Pakistan. Our system uses statistical analysis of dengue-related phone calls to accurately forecast suspected dengue cases 2 to 3 weeks ahead of time at a subcity level (correlation of up to 0.93). Our system has been operational at scale in Pakistan for the past 3 years and has received more than 300,000 phone calls. The predictions from our system are widely disseminated to public health officials and form a critical part of active government strategies for dengue containment. Our work is the first to demonstrate, with significant empirical evidence, that an accurate, location-specific disease forecasting system can be built using analysis of call volume data from a public health hotline.

Concepts: Scientific method, Regression analysis, Health, Epidemiology, Future, Forecasting, Telephone, Telephone exchange


OBJECTIVE The possible interaction of serum 25-hydroxyvitamin D [25(OH)D] and obesity in regard to type 2 diabetes and insulin resistance has not been well studied. To explore the effect modification of obesity on the association between 25(OH)D and insulin resistance/type 2 diabetes, data were examined from a nationally representative sample. RESEARCH DESIGN AND METHODS The analytic sample for the type 2 diabetes analysis (n = 12,900) was limited to participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2006 over 20 years of age. Participants >20 years of age assigned to the morning session and free of diabetes were limited to the insulin resistance analysis (n = 5,806). Multiplicative interaction was assessed through a cross-product interaction term in a multiple logistic regression model. The presence of additive interaction between insufficient 25(OH)D and obesity (indicated by BMI or waist circumference) was evaluated by calculation of the relative excess risk due to interaction (RERI) and attributable proportion due to interaction (AP). RESULTS There was no multiplicative interaction of insufficient 25(OH)D and obesity on type 2 diabetes or insulin resistance. Furthermore, none of the RERI or AP values were statistically significant in the diabetes analysis. However, there was strong additive interaction between abdominal obesity and insufficient 25(OH)D (RERI 6.45 [95% CI 1.03-11.52]) in regard to insulin resistance. In addition, 47% of the increased odds of insulin resistance can be explained by interaction between insufficient 25(OH)D and high BMI (AP 0.47 [95% CI 0.08-0.87]). CONCLUSIONS Within a cross-sectional, nationally representative sample, abdominal obesity and insufficient 25(OH)D interact to synergistically influence the risk of insulin resistance.

Concepts: Regression analysis, Vitamin D, Insulin, Diabetes mellitus type 2, Diabetes mellitus, Obesity, Insulin resistance, Metabolic syndrome


BACKGROUND: Physical and psychological problems after childbirth are common, and may have a significant negative and long-term impact on women’s wellbeing and daily functioning. The method of birth may be a particularly important factor influencing women’s health and wellbeing following birth, however, population-wide evidence is limited. This study uses data from 5,332 women who responded to a national survey of women’s experiences of maternity care in England. We examined women’s postnatal wellbeing in the first three months after birth, and whether these varied by mode of birth. METHODS: This is a secondary analysis of survey data using a random sample of women selected from birth registration. We used multinomial logistic regression models to examine the association between women’s self-reported psychological symptoms, health problems and mode of birth. RESULTS: Women who had forceps-assisted vaginal births and unplanned caesarean section births reported the poorest health and wellbeing, while those of women who had unassisted vaginal births and planned caesarean section births were less affected by the birth process. Most women’s physical and emotional health appeared to improve with time, however, those who had a forceps-assisted vaginal birth were more likely to report ongoing posttraumatic-type symptoms several months after the birth. CONCLUSIONS: Mode of birth was associated with differences in outcomes at three months. By comparison to women who had unassisted vaginal births, the risk of reduced postnatal health and wellbeing was higher amongst the women who had forceps-assisted vaginal births but not amongst women who had ventouse-assisted vaginal births. This would suggest that it is important to differentiate the different types of instrumental birth in outcome studies. Of concern was the higher rate of posttraumatic-type symptoms among women who had forceps-assisted vaginal births relative to the other modes of birth. Women who have forceps-assisted births should be monitored carefully by health professionals in the postnatal period, and in the months after childbirth, when they could be offered the opportunity to discuss their labour and birth.

Concepts: Regression analysis, Logistic regression, Childbirth, Obstetrics, Multinomial logit, Vagina, Caesarean section, Unassisted childbirth


We have identified a natural clay mixture that exhibits in vitro antibacterial activity against a broad spectrum of bacterial pathogens. We collected four samples from the same source and demonstrated through antibacterial susceptibility testing that these clay mixtures have markedly different antibacterial activity against Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA). Here, we used X-ray diffraction (XRD) and inductively coupled plasma - optical emission spectroscopy (ICP-OES) and - mass spectrometry (ICP-MS) to characterize the mineralogical and chemical features of the four clay mixture samples. XRD analyses of the clay mixtures revealed minor mineralogical differences between the four samples. However, ICP analyses demonstrated that the concentrations of many elements, Fe, Co, Cu, Ni, and Zn, in particular, vary greatly across the four clay mixture leachates. Supplementation of a non-antibacterial leachate containing lower concentrations of Fe, Co, Ni, Cu, and Zn to final ion concentrations and a pH equivalent to that of the antibacterial leachate generated antibacterial activity against E. coli and MRSA, confirming the role of these ions in the antibacterial clay mixture leachates. Speciation modeling revealed increased concentrations of soluble Cu(2+) and Fe(2+) in the antibacterial leachates, compared to the non-antibacterial leachates, suggesting these ionic species specifically are modulating the antibacterial activity of the leachates. Finally, linear regression analyses comparing the log10 reduction in bacterial viability to the concentration of individual ion species revealed positive correlations with Zn(2+) and Cu(2+) and antibacterial activity, a negative correlation with Fe(3+), and no correlation with pH. Together, these analyses further indicate that the ion concentration of specific species (Fe(2+), Cu(2+), and Zn(2+)) are responsible for antibacterial activity and that killing activity is not solely attributed to pH.

Concepts: Regression analysis, Bacteria, Pneumonia, Staphylococcus aureus, Antibiotic resistance, Escherichia coli, Chemistry, Methicillin-resistant Staphylococcus aureus